posted by user: marisavas_br || 3317 views || tracked by 4 users: [display]

WinDS 2017 : SIAM SDM'17 Workshop Women in Data Science


When Apr 27, 2017 - Apr 27, 2017
Where Houston, Texas, USA
Submission Deadline Jan 18, 2017
Notification Due Jan 30, 2017
Final Version Due Feb 6, 2017
Categories    computer science   data science   women

Call For Papers

First SIAM SDM Workshop Women in Data Science 2017 (WinDS)

April 27th, 2017, Houston, Texas, USA


The WinDS (Women in Data Science) workshop is a full-day event that will be held on April 27th in Houston, Texas in conjunction with SIAM International Conference on Data Mining (SDM 2017). This workshop event brings together female faculty, graduate students, research scientists and industry researchers for an opportunity to connect, exchange ideas and learn from each other in the field of Data Science. Underrepresented minorities, graduates, and undergraduates interested in pursuing data science, machine learning research are encouraged to participate. While most presenters should be women, everybody is invited to attend.

We will strongly encourage female students, post-docs and researchers in all areas of data mining, graph analytics, machine learning and applications in data science related to health, financial, sports, natural resource and so on.

Data science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, machine learning, data mining, and predictive analytics. Data science encompasses several areas such as data analytics, machine learning, statistics, optimization and managing big data.

WinDS will bring together women researchers and practitioners in the field to deal with the emerging challenges in processing both from theoretical and practical works on data science and advanced analytics.

General areas of interest to WinDS include but are not limited to:

- KDD Foundations and Data analytics,
- Machine learning and knowledge discovery
- Storage, retrieval, and search
- Privacy and security
- Applications, practices, tools, and evaluation

The full-day workshop will feature invited talks, contributed talks, and a short session on open problems and directions for future research.

The workshop solicits submissions for talks for both previously published and unpublished work. For unpublished work, authors can submit original work, unpublished ideas in the form of completed work or work-in-progress papers of up to 9 pages in length (excluding references). For previously published work, submitted papers must be no longer than 4 pages in length (excluding references). We particularly encourage papers that propose new research directions as well as interesting applications of data science.

We are using Easychair for submission: All full papers accepted should have a maximum length of 9 pages (single-spaced, 2 columns, 10-point font, and at least 1" margin on each
side) while short papers should have a maximum length 4 pages (same specification than full papers). Authors should use US Letter (8.5" x 11") paper size. Papers must have an abstract with a maximum of 300 words and a keyword list with no more than 6 keywords. Authors are required to submit their papers electronically in PDF format (postscript files can be converted using standard converters).

We would like to encourage you to prepare your paper in LaTeX2e. Papers should be formatted using the SIAM SODA macro, which is available through the SIAM website. You can access it at The filename is soda2e.all. Make sure you use the macros for SODA and Data Mining Proceedings; papers prepared using other proceedings macros will not be accepted. For Microsoft Word users, please convert your document to the PDF format.
All submissions should clearly present the author information including the names of the authors, the affiliations, and the emails. The main author should be a woman.

- Submission date: January 13th, 2017
- Notification date: January 30th, 2017
- Camera Ready: February 6th, 2017

- Ana Paula Appel - IBM Research - apappel AT
- Marisa Affonso Vasconcelos - IBM Research - marisaav AT
- Mirella M. Moro - Federal University of Minas Gerais (UFMG) - mirella AT
- Yasuko Matsubara - Kumamoto University - yasuko AT

Related Resources

SDM 2021   SIAM International Conference on Data Mining
AIP Journal - Indexed in Scopus 2021   Journal of Social and Business Informatics - Acta Informatica Pragensia
MDPI-SI-BDHA 2021   Call for Papers: Special Issue “Big Data for eHealth Applications” (MDPI Applied Sciences, IF 2.474 – Indexed on Scopus, Web of Science)
IWoSR 2021   2021 International Workshop on Service Robotics (IWoSR 2021)
ICDM 2021   21st IEEE International Conference on Data Mining
EI-CFAIS 2021   2021 International Conference on Frontiers of Artificial Intelligence and Statistics (CFAIS 2021)
CONF-CDS 2021   The 3rd International Conference on Computing and Data Science (CONF-CDS) Call for Papers
ECCSIT 2021   2021 European Conference on Computer Science and Information Technology (ECCSIT 2021)
CHEME 2021   5th International Conference on Chemical Engineering
DATA ANALYTICS 2021   The Tenth International Conference on Data Analytics